In the recent past, soft computing (SC) techniques are applied to complex and computationally intensive problems that have customarily proved intractable for conventional mathematical methods. Because of its proven strength in treating imprecise information and discovering novel solutions to hard problems, SC is still a topic of interest amongst researchers in various fields of science and engineering. Some popular SC paradigms include fuzzy computing, neural computing, evolutionary computing, and probabilistic reasoning. In general, SC intends to generate computing mechanisms that demonstrate useful properties, that is, formulating inference with vague and/or ambiguous data, adapting to dynamic environments, learning from noisy and/or incomplete information, and reasoning with uncertainties.

Application of SC to real-world problems is, however, complicated, as it associates several key issues (i.e., learning models, knowledge representation, evaluation criteria, etc.) requiring crucial options among several approaches proposed so far in this domain. Further, results and lessons learnt from the application of SC to real-world problems are of major significance for methodological research with the intention of refining the existing methods or devising new techniques.

The overall aim of this special issue is to compile the latest research and development, up-to-date issues, and challenges in the field of SC. Proposed submissions should be original, unpublished, and present novel in-depth fundamental research contributions either from a methodological perspective or from an application point of view. In particular, parallel and hybrid SC approaches and state-of-the-art reviews will also be entertained. Potential topics include, but are not limited to:

• Architectural design and development of new approaches combining fuzzy logic, neural networks, evolutionary computation, and other recent computational intelligence methods in the SC paradigm
• Comparative theoretical and empirical studies on SC techniques, with validation through convincing computational experiments, performance measures, and convergence proof
• Application of SC techniques (e.g., big data, smart systems, semantic web, sustainable development, cloud computing, dynamic processes, and other domains in science and engineering)

Before submission authors should carefully read over the journal’s Author Guidelines which are located at http://www.hindawi.com/journals/tswj/guidelines/. Prospective authors should submit an electronic copy of their complete manuscript through the journal Manuscript Tracking System at http://mts.hindawi.com/submit/journals/tswj/computer.science/soft/ according to the following timetable: